多部件系统维修决策及维修与备件库存联合决策研究

发布时间：2018-06-28 18:34

本文选题：多部件系统 + 维修决策　；参考：《太原科技大学》2015年博士论文

【摘要】：设备的维修与维修备件的库存管理互相影响和制约,将二者集成,寻找全局最优的联合策略是维修决策领域一个重要的研究方向。随着工业技术的日益发展,各类系统的复杂度不断提升,结构化和模块化的设计使得系统通常可以从功能和/或结构上划分为多个关键子系统或部件,且部件之间存在各种各样的依赖关系,为系统的维修决策研究带来了新的挑战,因此,考虑部件的相关性,研究多部件系统的维修决策及维修与备件库存的联合决策问题成为了亟需解决的新课题。本文针对在考虑部件相关性的多部件系统维修决策研究中存在的联合分布构建困难、枚举建模低效易错、仿真建模耗时和分解降维求解不准确等问题,研究多部件系统的维修决策建模与优化以及维修与备件库存联合决策的建模与优化问题,其主要研究工作如下:(1)多部件系统劣化状态空间划分建模方法研究。在分析并抽象基于不同基础策略的机会维修策略共同特征的基础上,构建了多部件系统统一的劣化状态空间划分建模方法,方法给出了联合劣化状态空间的表示与划分、维修需求组合的表示与划分及系统劣化状态空间区域与维修需求组合的对应关系;(2)相同和不相同多部件系统劣化状态空间划分建模研究。应用所提出的劣化状态空间划分方法,针对存在相关性的相同和不相同部件组成的多部件系统分别进行了统一的劣化状态空间划分建模,并给出了联合劣化状态稳态概率密度函数的计算模型和数值解法,推导了多部件系统维修需求组合概率的计算通式;(3)相同多部件系统和不相同两部件系统的视情机会维修决策建模与优化研究。针对不同系统的维修特性,制定了合理的视情机会维修策略,并在考虑各种维修要素的条件下,基于系统的联合劣化状态空间划分模型,建立了系统长期平均费用率模型,给出了优化方法,最后通过数值实验验证和分析了模型的正确性和方法的有效性;(4)相同多部件系统的维修与备件库存联合决策建模与优化研究。在劣化状态空间建模的基础上,给出了备件库存状态稳态概率的数值计算模型与解法,推导了受备件库存状态影响的维修活动的概率和备件的订购、持有概率的计算式,建立了维修与备件库存联合决策模型,给出了相应的优化方法,并以多个相同风力涡轮机的同一部件组成的系统为对象进行了应用研究;(5)不相同两部件系统的维修与备件库存联合决策建模与优化研究。在劣化状态与备件库存状态组合空间建模的基础上,给出了系统劣化与备件库存组合状态的稳态概率密度函数的计算模型与数值解法,推导了系统的维修活动、备件的订购和持有概率的计算方法,建立了系统的维修与备件库存联合决策模型,给出了相应的优化方法,并以单个风力涡轮机的两个关键部件组成的系统为对象进行了应用研究。
[Abstract]:The maintenance of equipment and the inventory management of maintenance spare parts affect and restrict each other. It is an important research direction in the field of maintenance decision to integrate the two strategies to find the global optimal joint strategy. With the development of industrial technology, the complexity of all kinds of systems is increasing. Structural and modular design make the system can be divided into several key subsystems or components from the function and / or structure. And there are a variety of dependencies between components, which brings new challenges to the research of system maintenance decision. Therefore, considering the correlation of components, The research on maintenance decision and joint decision of maintenance and spare parts inventory has become a new problem that needs to be solved. In this paper, it is difficult to construct joint distribution in the research of maintenance decision of multicomponent system considering component correlation, enumeration modeling is inefficient and error prone, simulation modeling is time-consuming and the solution of decomposition and dimension reduction is not accurate, and so on. The maintenance decision modeling and optimization of multicomponent system and the modeling and optimization of joint maintenance and spare parts inventory decision are studied. The main research work is as follows: (1) study on modeling method of multi-component system deterioration state space partition. On the basis of analyzing and abstracting the common characteristics of opportunity maintenance strategy based on different basic strategies, a unified modeling method of deteriorating state space partition for multi-component system is constructed, and the representation and partition of joint deterioration state space are given. The representation and partition of maintenance requirement combination and the corresponding relationship between the region of system deterioration state space and the combination of maintenance requirements; (2) the modeling of the partition of the same and different multi-component system deterioration state space. Based on the improved state space partitioning method, a unified decomposition model for the same and different components of multi-component systems with correlation is proposed. The calculation model and numerical solution of the steady-state probability density function of joint deterioration state are given. A general formula for calculating the combined probability of maintenance requirements of a multicomponent system is derived. (3) the opportunistic maintenance decision modeling and optimization of the same multi-component system and the different two-component system are studied. According to the maintenance characteristics of different systems, a reasonable opportunistic maintenance strategy is established. Under the condition that various maintenance elements are considered, the system long-term average cost rate model is established based on the joint deterioration state space partition model of the system. Finally, the correctness of the model and the validity of the method are verified and analyzed by numerical experiments. (4) the joint decision modeling and optimization of the maintenance and spare parts inventory of the same multi-component system are studied. On the basis of modeling of deterioration state space, a numerical calculation model and solution of steady state probability of spare parts inventory are given, and the probability of maintenance activities affected by spare parts inventory state and the order and holding probability of spare parts are deduced. The joint decision model of maintenance and spare parts inventory is established, and the corresponding optimization method is given. The system composed of the same parts of the same wind turbine is studied. (5) the joint decision modeling and optimization of the maintenance and spare parts inventory of the different two-component systems are studied. On the basis of modeling of the combined space of deterioration state and spare parts inventory state, the calculation model and numerical solution of steady-state probability density function of system deterioration and spare parts inventory combination state are given, and the maintenance activities of the system are deduced. The method of calculating the probability of ordering and holding of spare parts is presented. The joint decision model of system maintenance and spare parts inventory is established, and the corresponding optimization method is given. The application of the system composed of two key components of a single wind turbine is studied.
【学位授予单位】：太原科技大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TH17

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